Abdelkader BEHDENNA

Abdelkader BEHDENNA

University of Glasgow

H-index: 8

Europe-United Kingdom

Abdelkader BEHDENNA Information

University

University of Glasgow

Position

PostDoctoral researcher IBAHCM

Citations(all)

442

Citations(since 2020)

394

Cited By

180

hIndex(all)

8

hIndex(since 2020)

7

i10Index(all)

8

i10Index(since 2020)

6

Email

University Profile Page

University of Glasgow

Abdelkader BEHDENNA Skills & Research Interests

Genetics

Evolution

Bioinformatics

Top articles of Abdelkader BEHDENNA

From data disparity to data harmony: A comprehensive pan-cancer omics data collection

In cancer research, the exponential growth of omics datasets offers a significant opportunity for scientific advancement. However, challenges such as the lack of uniform standards, in both clinical and omic data, hinder the effective utilization of these datasets, thus impeding our understanding of cancer biology and the development of innovative therapeutic approaches.Addressing these challenges, we have created a novel collection of pan-cancer omics datasets with extensive clinical data harmonization and consistent omic data normalization.Here, we focused on patient-derived gene expression microarray datasets from the Gene Expression Omnibus database. To navigate the complexities presented by the diverse clinical descriptions inherent in these datasets, we leveraged our proprietary ontology, machine learning models, and domain expert quality control processes to homogenize the clinical data …

Authors

Lea Meunier,Guillaume Appe,Abdelkader Behdenna,Valentin Bernu,Helia Brull Corretger,Prashant Dhillon,Eleonore Fox,Julien Haziza,Charles Lescure,Camille Marijon,Clemence Petit,Solene Weill,Akpeli Nordor

Journal

Cancer Research

Published Date

2024/3/22

A scalable pancancer antigen target discovery platform for precision oncology

With the emergence of precision oncology as a new paradigm in cancer care, there is an urgent need to develop tools capable of mining the massive amounts of rich omic data generated every year. To support target discovery programs at scale, we developed a pan-cancer bioinformatics platform combining patient data with extensive biological and pharmaceutical knowledge for the identification and prioritization of novel antigen targets. Our pipeline was first validated with the discovery of new antigen targets amenable to CAR-T therapy for relapsed/refractory multiple myeloma. Here, we are exploring AML, a type of leukemia with several unmet needs. First, we identified and integrated 36 relevant microarray datasets from the GEO database using a proprietary data identification and integration pipeline. The clinical data was curated using our proprietary oncology ontology, machine learning models, and domain …

Authors

Eleonore Fox,Guillaume Appe,Abdelkader Behdenna,Lea Meunier,Akpeli Nordor,Solene Weill,Camille Marijon

Journal

Cancer Research

Published Date

2024/3/22

2P A machine learning-powered dashboard for the exploration of high-throughput transcriptomic datasets

BackgroundNCBI's Gene Expression Omnibus (GEO) is a major repository for high-throughput transcriptomic datasets. It currently contains approximately 7,000,000 transcriptomic profiles spread across more than 200,000 datasets, of which around 50,000 are related to cancer. The secondary analyses of these datasets hold vast potential to unlock new biological understanding and shape future clinical study designs. However, the high data heterogeneity and the limited browsing features of the repository’s website pose significant challenges, particularly in oncology research.MethodsHere, we introduce a solution that leverages a tagging approach for the characterization of GEO datasets. It focuses on the clinical description (metadata) of the sample transcriptomic profiles included in the datasets, and detects multiple criteria (eg, patient vs. cell line, donor type, overall survival, cancer type). This approach involves …

Authors

V Bernu,C Lescure,H Brull Corretger,P Dhillon,E Fox,C Marijon,A Nordor,C Petit,A Behdenna

Journal

ESMO Open

Published Date

2024/2/1

pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods

BackgroundVariability in datasets is not only the product of biological processes: they are also the product of technical biases. ComBat and ComBat-Seq are among the most widely used tools for correcting those technical biases, called batch effects, in, respectively, microarray and RNA-Seq expression data.ResultsIn this technical note, we present a new Python implementation of ComBat and ComBat-Seq. While the mathematical framework is strictly the same, we show here that our implementations: (i) have similar results in terms of batch effects correction; (ii) are as fast or faster than the original implementations in R and; (iii) offer new tools for the bioinformatics community to participate in its development. pyComBat is implemented in the Python language and is distributed under GPL-3.0 (https://www.gnu.org/licenses/gpl-3.0.en.html) license as a module of the inmoose package. Source code is available at https …

Authors

Abdelkader Behdenna,Maximilien Colange,Julien Haziza,Aryo Gema,Guillaume Appé,Chloé-Agathe Azencott,Akpéli Nordor

Journal

BMC bioinformatics

Published Date

2023/12/7

Introducing InMoose, an integrated open source Python package for multi-omic analyses

The recent exponential progress of sequencing technologies has dramatically impacted cancer research and paved the way to precision medicine in cancer care. In parallel, light-speed progress in bioinformatics has been essential to allow analysts to embrace the vast amount of data yielded by high-throughput profiling machines, turn this data into cancer biology knowledge, and ultimately develop innovative approaches to cancer care. Still, computational complexity and tools' interoperability remain major challenges for the advancement of -omic data-driven cancer research. Despite the historical prevalence of R, Python is gaining momentum in the bioinformatics landscape. As a general purpose language, it offers numerous advantages: - its overall ecosystem facilitates the integration of bioinformatics tools into large-scale frameworks, increasing their versatility and widening their targeted audience; - its …

Authors

Maximilien Colange,Guillaume Appé,Akpéli Nordor,Abdelkader Behdenna

Journal

Cancer Research

Published Date

2023/4/4

Integrating Transcriptomics and Proteomics for the Discovery of Novel Antigen Targets on Surface of Malignant Plasma Cells Amenable for Chimeric Antigen Receptor-T (CAR-T) Cell …

Though remarkable progress has been made in the field of multiple myeloma (MM), with proteasome inhibitors, immunomodulators and monoclonal antibodies, the disease is still currently incurable. Outcomes are dismal when patients become refractory to bortezomib, lenalidomide, pomalidomide and daratumumab (quadri-refractory). Several new treatment approaches, including enhanced monoclonal antibodies, antibody-drug conjugates (ADC), bispecific T-cell engagers (BiTE) and chimeric antigen-T-cell therapy (CAR-T) are under development. Antibody-based therapeutics targeting CD38 and SLAMF7 and a cellular therapy targeting BCMA have now been FDA-approved. However, most patients still relapse even after BCMA CAR-T infusion. New designs such as HLA-independent T cell receptors showed a high efficacy in the context of low antigen density, so new targets are now accessible for the treatment …

Authors

Alexis Talbot,Solène Weill,Eléonore Fox,Léa Meunier,Guillaume Appé,Camille Marijon,Abdelkader Behdenna,Arun P Wiita,Akpéli Nordor,Justin Eyquem

Journal

Blood

Published Date

2022/11/15

A minimal yet flexible likelihood framework to assess correlated evolution

An evolutionary process is reflected in the sequence of changes of any trait (e.g., morphological or molecular) through time. Yet, a better understanding of evolution would be procured by characterizing correlated evolution, or when two or more evolutionary processes interact. Previously developed parametric methods often require significant computing time as they rely on the estimation of many parameters. Here, we propose a minimal likelihood framework modeling the joint evolution of two traits on a known phylogenetic tree. The type and strength of correlated evolution are characterized by a few parameters tuning mutation rates of each trait and interdependencies between these rates. The framework can be applied to study any discrete trait or character ranging from nucleotide substitution to gain or loss of a biological function. More specifically, it can be used to 1) test for independence between two …

Authors

Abdelkader Behdenna,Maxime Godfroid,Patrice Petot,Joël Pothier,Amaury Lambert,Guillaume Achaz

Journal

Systematic Biology

Published Date

2022/7/1

We are what we eat, plus some per mill: Using stable isotopes to estimate diet composition in Gyps vultures over space and time

Dietary studies in birds of prey involve direct observation and examination of food remains at resting and nesting sites. Although these methods accurately identify diet in raptors, they are time‐consuming, resource‐intensive, and associated with biases from the feeding ecology of raptors like Gyps vultures. Our study set out to estimate diet composition in Gyps vultures informed by stable isotopes that provide a good representation of assimilated diet from local systems. We hypothesized that differences in Gyps vulture diet composition is a function of sampling location and that these vultures move between Serengeti National Park and Selous Game Reserve to forage. We also theorized that grazing ungulates are the principal items in Gyps vulture diet. Through combined linear and Bayesian modeling, diet derived from δ13C in Gyps vultures consisted of grazing herbivores across sites, with those in Serengeti …

Authors

Allan A Baino,Grant GJC Hopcraft,Corinne J Kendall,Jason Newton,Abdelkader Behdenna,Linus K Munishi

Journal

Ecology and Evolution

Published Date

2022/3

Trends in bacterial bloodstream infections and resistance in immuno-compromised patients with febrile neutropenia: a retrospective analysis

Bacterial infections remain a major cause of morbidity and mortality in immunocompromised children. From the onset of fever, an early administration of broad-spectrum antibiotics is begun; this strategy could induce emergence of multi-drug resistant bacteria (MDR). We describe the incidence and microbiological spectrum, including MDR bacteria of bacterial documented blood-stream infections (BSI) in immunocompromised children. A retrospective, descriptive study was conducted in a tertiary referral centre in France from January 2014 to December 2017. Our cohort included a large scale of patients with febrile neutropenia: haematological and oncological malignancies, haematopoietic stem cell transplantations, severe combined immunodeficiency syndromes. BSI were defined by positive blood culture samples associated with fever. Among 760 febrile neutropenia episodes in 7301 admitted patients …

Authors

Coralie Raad,Abdelkader Behdenna,Christine Fuhrmann,Cécile Conter,Daniela Cuzzubbo,Jean-Philippe Rasigade,Yves Bertrand,Carine Domenech

Journal

European Journal of Pediatrics

Published Date

2021/9

Predicting the presence and titre of rabies virus‐neutralizing antibodies from low‐volume serum samples in low‐containment facilities

Serology is a core component of the surveillance and management of viral zoonoses. Virus neutralization tests are a gold standard serological diagnostic, but requirements for large volumes of serum and high biosafety containment can limit widespread use. Here, focusing on Rabies lyssavirus, a globally important zoonosis, we developed a pseudotype micro‐neutralization rapid fluorescent focus inhibition test (pmRFFIT) that overcomes these limitations. Specifically, we adapted an existing micro‐neutralization test to use a green fluorescent protein‐tagged murine leukaemia virus pseudotype in lieu of pathogenic rabies virus, reducing the need for specialized reagents for antigen detection and enabling use in low‐containment laboratories. We further used statistical models to generate rapid, quantitative predictions of the probability and titre of rabies virus‐neutralizing antibodies from microscopic imaging of …

Authors

Diana K Meza,Alice Broos,Daniel J Becker,Abdelkader Behdenna,Brian J Willett,Mafalda Viana,Daniel G Streicker

Journal

Transboundary and Emerging Diseases

Published Date

2021/5

See List of Professors in Abdelkader BEHDENNA University(University of Glasgow)

Abdelkader BEHDENNA FAQs

What is Abdelkader BEHDENNA's h-index at University of Glasgow?

The h-index of Abdelkader BEHDENNA has been 7 since 2020 and 8 in total.

What are Abdelkader BEHDENNA's top articles?

The articles with the titles of

From data disparity to data harmony: A comprehensive pan-cancer omics data collection

A scalable pancancer antigen target discovery platform for precision oncology

2P A machine learning-powered dashboard for the exploration of high-throughput transcriptomic datasets

pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods

Introducing InMoose, an integrated open source Python package for multi-omic analyses

Integrating Transcriptomics and Proteomics for the Discovery of Novel Antigen Targets on Surface of Malignant Plasma Cells Amenable for Chimeric Antigen Receptor-T (CAR-T) Cell …

A minimal yet flexible likelihood framework to assess correlated evolution

We are what we eat, plus some per mill: Using stable isotopes to estimate diet composition in Gyps vultures over space and time

...

are the top articles of Abdelkader BEHDENNA at University of Glasgow.

What are Abdelkader BEHDENNA's research interests?

The research interests of Abdelkader BEHDENNA are: Genetics, Evolution, Bioinformatics

What is Abdelkader BEHDENNA's total number of citations?

Abdelkader BEHDENNA has 442 citations in total.

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